#add parent dir to find package. Only needed for source code build, pip install doesn't need it.
import os, inspect
currentdir = os.path.dirname(os.path.abspath(inspect.getfile(inspect.currentframe())))
parentdir = os.path.dirname(os.path.dirname(currentdir))
os.sys.path.insert(0,parentdir)

import gym
import numpy as np
import pybullet as p
import pybulletgym.envs
import os.path
import time


def relu(x):
    return np.maximum(x, 0)


class SmallReactivePolicy:
    "Simple multi-layer perceptron policy, no internal state"
    def __init__(self, observation_space, action_space):
        assert weights_dense1_w.shape == (observation_space.shape[0], 256)
        assert weights_dense2_w.shape == (256, 128)
        assert weights_final_w.shape  == (128, action_space.shape[0])

    @staticmethod
    def act(ob):
        x = ob
        x = relu(np.dot(x, weights_dense1_w) + weights_dense1_b)
        x = relu(np.dot(x, weights_dense2_w) + weights_dense2_b)
        x = np.dot(x, weights_final_w) + weights_final_b
        return x


def main():
    print("create env")
    env = gym.make("HumanoidFlagrunHarderPyBulletEnv-v0")
    env.render(mode="human")
    pi = SmallReactivePolicy(env.observation_space, env.action_space)

    while 1:
        frame = 0
        score = 0
        restart_delay = 0
        obs = env.reset()
        torsoId = -1
        for i in range (p.getNumBodies()):
          print(p.getBodyInfo(i))
          if p.getBodyInfo(i)[0].decode() == "torso":
            torsoId=i
            print("found humanoid torso")

        while 1:
            time.sleep(0.02)
            a = pi.act(obs)
            obs, r, done, _ = env.step(a)
            score += r
            frame += 1
            humanPos, humanOrn = p.getBasePositionAndOrientation(torsoId)
            camInfo = p.getDebugVisualizerCamera()
            curTargetPos = camInfo[11]
            distance=camInfo[10]
            yaw = camInfo[8]
            pitch=camInfo[9]
            targetPos = [0.95*curTargetPos[0]+0.05*humanPos[0],0.95*curTargetPos[1]+0.05*humanPos[1],curTargetPos[2]]
            p.resetDebugVisualizerCamera(distance, yaw, pitch, targetPos)

            still_open = env.render("human")
            if still_open is None:
                return
            if not done:
                continue
            if restart_delay == 0:
                print("score=%0.2f in %i frames" % (score, frame))
                restart_delay = 60*2  # 2 sec at 60 fps
            else:
                restart_delay -= 1
                if restart_delay == 0:
                    break

weights_dense1_w = np.array([
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weights_dense2_b = np.array([ -0.1167, -0.0510, +0.1155, +0.2151, -0.0416, +0.1452, -0.0794, +0.1217, -0.0268, +0.1016, +0.1274, -0.0271, -0.1298, +0.0793, +0.0404, +0.0955, -0.0855, -0.0578, +0.3129, +0.0950, -0.0090, -0.0090, +0.2334, +0.1715, +0.1043, +0.0024, -0.0009, +0.0342, +0.0742, +0.1323, +0.0760, -0.0173, -0.0577, +0.1013, +0.0974, -0.0338, +0.0429, +0.3263, +0.1869, +0.1798, -0.0126, -0.1002, +0.1193, +0.1248, -0.1544, +0.1357, -0.0956, +0.1405, +0.1551, +0.4303, +0.1871, -0.0234, +0.1528, +0.3371, +0.3916, +0.2319, +0.1516, +0.1534, +0.1397, -0.1125, -0.0907, +0.0794, -0.0481, +0.1252, -0.0279, +0.0712, -0.0944, +0.2633, +0.0062, -0.0458, +0.2715, +0.1041, -0.1381, -0.0402, +0.1133, -0.0761, +0.1408, +0.2070, -0.0576, -0.1057, -0.0464, +0.1069, -0.0581, +0.2263, +0.0632, -0.0277, +0.0625, +0.2455, +0.1857, -0.0172, -0.0332, -0.0384, +0.1591, +0.1721, +0.1568, +0.1680, +0.0232, +0.1134, +0.2353, +0.0235, +0.1007, -0.0667, -0.1689, +0.1512, +0.1154, -0.0607, +0.3318, +0.1063, +0.2589, +0.3722, -0.0955, +0.1107, +0.0735, +0.0284, +0.2233, -0.0427, +0.1083, +0.2224, +0.1169, +0.3346, -0.0581, +0.1114, +0.0446, +0.0422, +0.1618, +0.1712, +0.1250, +0.0345])

weights_final_w = np.array([
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])

weights_final_b = np.array([ +0.0149, +0.1334, -0.1019, -0.0498, +0.0919, -0.2079, +0.1914, -0.0708, +0.0737, -0.1228, +0.0112, -0.0441, +0.0087, -0.1149, +0.0063, +0.0170, -0.0965])

if __name__ == "__main__":
    main()
